Influence of leg preference on bilateral muscle activation during cycling

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Influence of leg preference on bilateral muscleactivation during cyclingFelipe P. Carpes a , Fernando Diefenthaeler b , Rodrigo R. Bini c , Darren J. Stefanyshyn d ,Irvin E. Faria e & Carlos B. Mota fa Center for Health Sciences , Universidade Federal do Pampa , Uruguaiana, Brazilb Laboratory of Biomechanics , Federal University of Santa Catarina , Florianópolis, Brazilc Sport Performance Research Institute New Zealand , AUT University , Auckland, NewZealandd Human Performance Laboratory , The University of Calgary , Calgary, Alberta, Canadae Department of Kinesiology and Health Science , California State University , Sacramento,California, USAf Laboratory of Biomechanics , Universidade Federal de Santa Maria , Santa Maria, BrazilPublished online: 29 Nov 2010.

To cite this article: Felipe P. Carpes , Fernando Diefenthaeler , Rodrigo R. Bini , Darren J. Stefanyshyn , Irvin E. Faria &Carlos B. Mota (2011) Influence of leg preference on bilateral muscle activation during cycling, Journal of Sports Sciences,29:2, 151-159, DOI: 10.1080/02640414.2010.526625

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Influence of leg preference on bilateral muscle activation during cycling

FELIPE P. CARPES1, FERNANDO DIEFENTHAELER2, RODRIGO R. BINI3,

DARREN J. STEFANYSHYN4, IRVIN E. FARIA5, & CARLOS B. MOTA6

1Center for Health Sciences, Universidade Federal do Pampa, Uruguaiana, Brazil, 2Laboratory of Biomechanics, Federal

University of Santa Catarina, Florianopolis, Brazil, 3Sport Performance Research Institute New Zealand, AUT University,

Auckland, New Zealand, 4Human Performance Laboratory, The University of Calgary, Calgary, Alberta, Canada,5Department of Kinesiology and Health Science, California State University, Sacramento, California, USA, and 6Laboratory

of Biomechanics, Universidade Federal de Santa Maria, Santa Maria, Brazil

(Accepted 21 September 2010)

AbstractThe purpose of this study was to investigate asymmetry of muscle activation in participants with different levels of experienceand performance with cycling. Two separate experiments were conducted, one with nine cyclists and one with nine non-cyclists. The experiments involved incremental maximal and sub-maximal constant load cycling tests. Bilateral surfaceelectromyography (EMG) and gross and net muscle efficiency were assessed. Analyses of variance in mixed linear modelsand t-tests were conducted. The cyclists in Experiment 1 presented higher gross efficiency (P5 0.05), whereas net efficiencydid not differ between the two experiments (21.3+ 1.4% and 19.8+ 1.0% for cyclists and non-cyclists, respectively). Theelectrical muscle activity increased significantly with exercise intensity regardless of leg preference in both experiments. Thecoefficient of variation of EMG indicated main effects of leg in both experiments. The non-preferred leg of non-cyclists(Experiment 2) presented statistically higher variability of muscle activity in the gastrocnemius medialis and vastus lateralis.Our findings suggest similar electrical muscle activity between legs in both cyclists and non-cyclists regardless of exerciseintensity. However, EMG variability was asymmetric and appears to be strongly influenced by exercise intensity for cyclistsand non-cyclists, especially during sub-maximal intensity. Neural factors per se do not seem to fully explain previous reportsof pedalling asymmetries.

Keywords: Functional laterality, lower extremity, limb preference, performance asymmetry, motor performance, learning

Introduction

Limb preference has been the subject of several

investigations that overwhelmingly support an asso-

ciation between preference and performance of the

upper limbs (for a review, see Serrien, Ivry, &

Swinnen, 2006). Many of these studies reported an

advantage of the preferred over the contralateral limb

in terms of neuromuscular control, such as lower

magnitude of muscle activation and frequency

during dynamic tasks (Adam, De Luca, & Erim,

1998; De Luca, Sabbahi, & Roy, 1986; Diederichsen

et al., 2007). If long-term unilateral recruitment

leads to performance asymmetry in favour of the

preferred upper limb, lower extremity performance

might be anticipated to be symmetrical due to its

usual bilateral recruitment, for instance during

locomotion.

Nevertheless, asymmetry in isometric plantar

flexion torque accompanied by significantly lower

surface electromyography (EMG) median frequency

in the tibialis anterior and gastrocnemius (medial

head) was observed in favour of the preferred leg of

middle-aged people (Valderrabano et al., 2007). In

addition, asymmetries in force, crank torque or work,

power output, and kinematics were observed during

cycling (Carpes, Rossato, Faria, & Mota, 2007a,

2007b; Cavanagh, Petak, Shapiro, & Daly, 1974;

Daly & Cavanagh, 1976; Edeline, Polin, Tourny-

Chollet, & Weber, 2004; Sanderson, Hennig, &

Black, 1991; Sargeant & Davies, 1977; Smak,

Neptune, & Hull, 1999). Kinetic asymmetries (crank

torque and pedal forces) ranged from 5 to 20% in

favour of the preferred limb, and appeared to be

inversely related to exercise intensity during pedal-

ling (Carpes et al., 2007a; Sanderson et al., 1991).

Correspondence: F. P. Carpes, Center for Health Sciences, Universidade Federal do Pampa, BR 472, km 592, PO Box 118, Uruguaiana, RS 97500-970, Brazil.

E-mail: [email protected]

Journal of Sports Sciences, January 15th 2011; 29(2): 151–159

ISSN 0264-0414 print/ISSN 1466-447X online � 2011 Taylor & Francis

DOI: 10.1080/02640414.2010.526625

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Kinematic asymmetry also appears to be dependent

on cycling intensity, especially for non-cyclists

(Edeline et al., 2004). These studies support the

assumption that asymmetries during cycling reduce

as the workload increases during incremental or

constant load exercise.

While a high workload is associated with pedalling

symmetry in cyclists, it is also related to muscle

fatigue. Fatigue is known to influence the synchro-

nization of motor units (Boonstra et al., 2008) and to

increase muscle activation due to recruitment of

additional motor units (Hug & Dorel, 2009). It is

also related to release of inhibitory pathways in

sensorimotor areas (Kapreli et al., 2006) that could

increase the similarity in bilateral input (Boonstra

et al., 2008). It facilitates excitability and neural

coupling by inter-hemispheric cortical communica-

tion (Glass, 2001), which is one factor that mini-

mizes lateral differences (Anguera, Russell, Noll, &

Seidler, 2007; Seidler & Noll, 2008; Teixeira &

Caminha, 2003). Therefore, the symmetry in muscle

activation as exercise workload increases could

support a role of neural factors on force asymmetries

(Simon & Ferris, 2008), which would be consistent

with a reduction of asymmetry at highest exercise

intensities (Carpes et al., 2007b) supported by

fatigue effects on motor unit recruitment (Boonstra

et al., 2008).

However, as denoted in a recent review (Hug &

Dorel, 2009), no research has addressed bilateral

muscle activation and asymmetries in cyclists and

non-cyclists during bouts of maximal and sub-

maximal exercise. Considering these previous reports,

we hypothesize asymmetry in muscle activation

during cycling, with its magnitude dependent on the

exercise intensity for cyclists and non-cyclists. The

preferred leg could present improved muscle activa-

tion, which would be more marked for individuals

with cycling experience. To test this hypothesis, we

quantified bilateral muscle activation of the lower

limbs in cyclists and healthy non-cyclists during two

cycling protocols.

Methods

Participant recruitment

Eighteen individuals signed an informed consent

form in agreement with the local ethics committee

(IRB #2007945) and principles outlined in the

Declaration of Helsinki for voluntary participation

in the study. Participants in Experiment 1 were

cyclists who had been training continuously for at

least 3 years. Participants in Experiment 2 were non-

cyclists, but physically well conditioned. Experi-

ments involved an incremental maximal cycling

performance and a constant load trial lasting up to

12 min. Leg preference was identified for each

participant by means of the revised Waterloo Inven-

tory (Elias, Bryden, & Bulman-Fleming, 1998). Our

interest in evaluation of lateral differences was not

explained to the participants, as such information

might have altered their pedalling mechanics. Partici-

pants were instructed to refrain from intense exercise

and keep to their normal diet the day before the trials.

Experiment 1 – cyclists’ assessment

Experiment 1 consisted of nine trained male cyclists

(mean age 27.6 years, s¼ 6; height 1.77 m, s¼ 0.09;

body mass 73 kg, s¼ 8) whose average weekly

training volume was 350 km (s¼ 80). These partici-

pants performed an incremental maximal test and a

constant load cycling test. Cyclists brought their own

bicycle and cycling equipment to the laboratory.

Each participant’s bicycle was mounted on a

stationary cycling simulator (Computrainer ProLab

3D, Racermate Inc., Seattle, WA, USA) for testing.

The cycling simulator controlled the exercise work-

load and recorded power output and cadence

throughout the incremental maximal and constant

load tests. All cyclists used clipless pedals.

Incremental maximal test. The incremental maximal

test began at a workload of 50 W and increased

25 W every minute until exhaustion (Lucia, Hoyos,

Perez, Santalla, & Chicharro, 2002). Exhaustion was

defined as the moment that a participant was no

longer capable of maintaining the preferred cadence.

Maximal power output was defined as the last entire

stage completed. Maximal oxygen uptake was

defined as the highest average oxygen uptake

( _V O2) over a 30-s period, and the second ventilatory

threshold was determined by the ventilatory equiva-

lent method (Wasserman, Van Kessel, & Burton,

1967). Participants were asked to maintain their

preferred pedalling cadence during the trials. Gas

exchange and muscle activation were monitored

throughout the incremental maximal test and ana-

lysed according to intensities corresponding to 40,

60, 80, and 100% of the individual maximal

power output (Hug, Bendahan, Le Fur, Cozzone,

& Grelot, 2004a). During the incremental maximal

and subsequent constant load test, gas exchange was

monitored breath-by-breath using an open-circuit

indirect gas exchange system (MGC CPX/D, Med-

ical Graphics Corp., St. Louis, MO, USA). Before

each trial, the oxygen and carbon dioxide analysers

were calibrated using previously calibrated medical

grade gases that spanned air in the physiological

range. Muscle activation signals were amplified

and recorded at a sampling rate of 2000 Hz with

14-bit resolution using Miograph systems (MioTec

Biomedical, Porto Alegre, RS, Brazil).

152 F. P. Carpes et al.

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Constant-load test. Following a rest of 60–90 min

after the incremental exercise, cyclists performed the

constant load trial. Such a rest period should

provide enough time for muscle recovery due to

the aerobic fitness of the participant (for a review,

see McMahon & Jenkins, 2002). In addition, it

permitted the athletes to visit the laboratory on only

one occasion and did not disturb their training

programme during the week. Before the test

commenced, the resting metabolic cost was mea-

sured during 5 min of sitting in a chair. The

workload for this test was set at the power output

eliciting 70% of the workload corresponding to the

second ventilatory threshold. This sub-maximal

intensity was selected in an attempt to avoid the

occurrence of the slow component of oxygen uptake

during the constant load trial, which could influence

efficiency and muscle activation measurements

(Poole et al., 1991).

Gas exchange, for calculation of muscle efficiency,

and electrical muscle activation, for root-mean-

square analysis, were recorded throughout the trial.

Muscle efficiency was computed and the muscle

activation was recorded for a period of 5 min during

which there were no significant changes in oxygen

uptake. From the 5-min steady-state period, the

average of minutes 3 and 4 was used for all statistical

analyses.

Variables. During the incremental and constant load

tests, the _V O2, carbon dioxide production ( _V CO2),

and the respiratory exchange ratio were measured

continuously and related to the workload. During the

constant load test, gas exchange data were used for

estimation of gross and net efficiency. Gross effi-

ciency was calculated as the ratio of mechanical work

per minute (i.e. watts converted to kcal � min71) to

energy expenditure per minute estimated from

oxygen uptake and the respiratory exchange ratio

using Lusk’s tables (i.e. kcal � min71) (Sidossis,

Horowitz, & Coyle, 1992). Net efficiency was

calculated as the ratio of mechanical work (i.e. watts

converted to kcal � min71) to energy expenditure

above the metabolic cost at rest (i.e. kcal � min71)

(Gaesser & Brooks, 1975).

Electrical muscle activation was monitored by

means of surface electromyography from the right

and left vastus lateralis, biceps femoris, and gastro-

cnemius (medial head) during both incremental

maximal and constant load tests. Pairs of Ag/AgCl

electrodes (bipolar configuration) with a diameter of

22 mm (Kendall Meditrace, Chicopee, Canada)

were positioned on the skin after careful shaving

and cleaning of the area with an abrasive cleaner and

alcohol swabs to reduce the skin impedance (De

Luca, 1997). A reference electrode placed over the

skin of the acromion served as a neutral site. The

electrodes were placed over the belly of the muscles,

parallel with the orientation of the muscle fibres

(Hermens, Freriks, Disselhorst-Klug, & Rau, 2000)

and taped to the skin using micropore tape (3M

Company, St Paul, MN, USA) to minimize move-

ment artifact.

The raw EMG signals were smoothed with a

fourth-order band-pass Butterworth digital filter at

10–500 Hz. After full-wave rectification and offset

correction, the onset and offset of EMG activity were

determined by the signal’s variation two standard

deviations above the baseline value recorded between

each EMG burst (Hodges & Bui, 1996). The average

root-mean-square value calculated from 12 pedal

revolutions was used to indicate the magnitude of

muscle activation (Moritani, Muro, & Nagata, 1986;

Ryan & Gregor, 1992). Offline analyses of EMG

signals were developed with custom-written scripts

(MATLAB 7.0, Mathworks Inc., Novi, MI, USA).

For each participant and each muscle, the calculated

root-mean-square values were expressed as a per-

centage of the individual maximal root-mean-square

value found during the incremental test (Gamet,

Duchene, & Goubel, 1996; Hug et al., 2004a;

Laplaud, Hug, & Grelot, 2006), in an attempt to

minimize normalization errors (Mirka, 1991).

Statistical procedures. After visual inspection, descrip-

tive statistics (means and standard deviations) were

calculated. The data variability for the root-mean-

square values was expressed by calculating the

coefficient of variation among the participants.

Normality and sphericity of the data were verified

by Shapiro-Wilk’s and Mauchly’s test, respectively.

The equality of variances was tested using Levene’s

test. Non-parametric data sets were compared using

the correlated non-parametric test. For data from the

incremental maximal test, for each muscle and leg,

the normalized root-mean-square values were com-

pared between the intensities using analysis of

variance (ANOVA) with post-hoc Bonferroni tests.

The EMG coefficient of variation was compared

between legs and intensities with ANOVA for a

mixed linear model (2 legs6 4 intensities) using a

Bonferroni correction for multiple comparisons.

Data on EMG variability from the constant load test

were compared between legs using independent

t-tests. Statistical significance was set at P5 0.05

for all data analysis using SPSS v.13 (SPSS Inc.,

Chicago, IL, USA).

Experiment 2 – non-cyclists’ assessment

The non-cyclist group consisted of seven male and

two female university students (mean age 24 years,

s¼ 3; height 1.76 m, s¼ 0.08; body mass 75 kg,

s¼ 11). They were healthy and physically active

Leg preference and pedalling asymmetry 153

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enough to perform the trials successfully, but were

not involved in any systematic lower limb training.

They performed the cycling trials using a cycle

simulator (Velotron Dynafit Pro, Racermate Inc.,

Seattle, WA, USA), which was properly fitted for

each participant’s anthropometric characteristics. All

non-cyclists used toe-clip pedals in line with their

previous recreational experience.

Incremental maximal test. Non-cyclists completed an

incremental maximal test beginning at a workload of

50 W that was increased by 25 W every 3 min. This

was done to decrease the difficulty of the test without

influencing the detection of the second ventilatory

threshold, which was our purpose for the incremental

maximal test. Exhaustion, maximal power output,

maximal oxygen uptake, and the second ventilatory

threshold were determined as described for Experi-

ment 1. Participants maintained their preferred

pedalling cadence during the trials with the help of

visual cadence feedback. Gas exchange and muscle

activation were analysed according to intensities

corresponding to 40, 60, 80, and 100% of the

individual maximal power output (Hug et al.,

2004a). Gas exchange was sampled continuously

from a mixing chamber where samples were then

drawn into the oxygen and carbon dioxide analysers

for continuous measurement using a metabolic cart

(TrueOne 2400, Parvo Medics, Salt Lake City,

UT, USA). Before each trial, the oxygen and

carbon dioxide analysers were properly calibrated

according to manufacturer’s recommendations. The

EMG signals in Experiment 2 were recorded at a

sampling rate of 2400 Hz with 12-bit resolution

using a Biovision EMG system (Biovision Inc.,

Wehrheim, Germany) during the last minute of each

workload.

Constant-load test. The test protocol was performed in

the same way as described for Experiment 1.

Participants had visual information from cadence

feedback to ensure that they maintained a similar

pedalling rate throughout the test.

Variables. Experiment 2 evaluated non-cyclists for

the same variables recorded in Experiment 1: _V O2,_V CO2, and respiratory exchange ratio were mea-

sured continuously and related to the workload for

estimation of gross (Sidossis et al., 1992) and net

muscle efficiency (Gaesser & Brooks, 1975). Elec-

trical muscle activation was monitored by means of

surface electromyography (EMG) from the right and

left vastus lateralis, biceps femoris, and gastrocne-

mius (medial head). Raw EMG signals were

smoothed with a fourth-order band-pass Butterworth

digital filter at 10–500 Hz. Root-mean-square values

were computed as described above.

Statistical procedures. The procedures for statistical

data analysis in Experiment 2 were the same as for

Experiment 1.

Results

Experiment 1 – cyclists’ assessment

Participants in Experiment 1 had a mean maximal

oxygen uptake ( _V O2max) of 4.42+ 0.5 litres �min71, mean maximal power output of 367+52 W, and mean power output of 311+ 45 W at

the second ventilatory threshold. Averaged pedalling

cadence during the incremental maximal test was

91+ 6 rev � min71, which was sustained during the

constant load test (average cadence of 91+ 5

rev � min71). As stated previously, during the con-

stant load test, all participants exercised at the

workload eliciting 70% of the workload at the second

ventilatory threshold (average power output of

218+ 32 W). This ensured that the participants

exercised at a similar relative exercise intensity.

During this trial, participants presented gross muscle

efficiency of 21.3+ 1.4% and net muscle efficiency

of 24+ 1.3%.

The increase in root-mean-square values during

the incremental test in Experiment 1 suggested

progressive muscle recruitment in the vastus

lateralis and biceps femoris from both legs (Figure

1). Biceps femoris activation showed a main effect

of intensity for the preferred (F3,24¼ 76.12;

P5 0.01) and non-preferred leg (F3,24¼ 42.35;

P5 0.01) but no interactions were observed. For

gastrocnemius medialis, no main effects were

found in the incremental test. The vastus lateralis

also showed a main effect of intensity for both the

preferred (F3,24¼ 212.80; P5 0.01) and non-pre-

ferred leg (F3,24¼ 98.89; P5 0.01). Root-mean-

square did not differ between the preferred and

non-preferred leg, but the comparisons across

intensities within legs support progressive muscular

recruitment in the vastus lateralis and biceps

femoris in both the preferred and non-preferred

leg.

During the incremental test, the EMG coefficient

of variation decreased as the workload increased

(Table I). The group variability was statistically

higher (P5 0.05) in the non-preferred leg of

cyclists in Experiment 1 for most muscles and

intensities, except for gastrocnemius medialis at

40% and vastus lateralis at 60% of maximal power

output.

During the constant load trial, variability did not

differ between legs of the cyclists (Table II). There-

fore, symmetry in muscle activation was observed, as

well as similar group variability between legs during

the sub-maximal trial.


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Experiment 2 – non-cyclists’ assessment

Participants in Experiment 2 had a mean _V O2max of

3.48+ 0.41 litres � min71, mean maximal power

output of 225+ 38 W, and mean power output of

192+ 33 W at the second ventilatory threshold.

During the constant load trial, participants cycled

at the same relative intensity (power output of

134+ 23 W), which was determined by the work-

load eliciting 70% of the workload at the second

ventilatory threshold. They presented gross muscle

efficiency of 19.8+ 1% and net muscle efficiency of

24.1+ 0.7%.

In the incremental test, average cadence was

72+ 8 rev � min71, and during the constant load

trial cadence was 70+ 5 rev � min71. During the

incremental maximal test, changes in root-mean-

square values in Experiment 2 suggested progres-

sive muscle recruitment in both the preferred and

non-preferred leg (Figure 2), as observed in

Experiment 1. Biceps femoris activation showed a

main effect of intensity for the preferred (F3,24¼11.60; P5 0.01) and non-preferred leg (F3,24¼8.53; P5 0.01). For gastrocnemius medialis of the

preferred and non-preferred leg, no main effects

were found in the incremental test. Vastus lateralis

also showed a main effect of intensity for both

the preferred (F3,24¼ 17.10; P5 0.01) and non-

preferred leg (F3,24¼ 56.87; P5 0.01). Root-mean-

square group variability during the incremental

maximal test did not support a direct relationship

between variability and asymmetry in favour of a

given leg. Group variability was higher in the non-

preferred biceps femoris of non-cyclists, but for the

gastrocnemius medialis and vastus lateralis all

statistically significant differences between legs were

related to higher variability of the preferred leg

(Table III).

The group variability was significant higher

(P5 0.05) in the non-preferred gastrocnemius med-

ialis and vastus lateralis muscles. Muscle activation

data are presented in Table IV.

Figure 1. Mean and standard deviation root-mean-square (RMS)

values normalized by the maximal RMS observed in the incremental

test (RMS normalized) for biceps femoris, gastrocnemius (medial

head), and vastus lateralis for the preferred (P) and non-preferred

(NP) leg of participants in Experiment 1. Results from each muscle

are presented for intensities of 40%, 60%, 80%, and 100% of

maximal power output. For both legs, RMS increased significantly

as the exercise intensity increased (#P50.05 between intensities),

except for gastrocnemius. No differences were observed between

the preferred and non-preferred leg.

Table I. Coefficients of variation (expressed as percentages) for EMG signals obtained in the incremental test of Experiment 1.

Muscle Leg

Intensities (% of maximal power output)

40% 60% 80%

Biceps femoris Preferred 16.9+ 3.0 17.1+ 2.7 11.2+ 1.2

Non-preferred 27.5+ 6.6* 22.7+ 5.7* 13.0+ 1.7*

Gastrocnemius Preferred 12.1+ 1.5 7.4+ 0.5 7.6+ 0.6

Non-preferred 11.7+ 1.3 15.1+ 2.4* 11.0+ 1.2*

Vastus lateralis Preferred 15.5+ 2.5 11.2+ 1.2 7.8+ 0.6

Non-preferred 19.4+ 3.6* 11.0+ 1.5 13.1+ 1.8*

Note: The 100% intensity was not considered due to a standard deviation equal to zero in most cases. Data are presented as group

mean+ standard deviation for each muscle, intensity, and leg.

*Significant difference between legs (P50.05).


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Discussion

Main findings

Previous researchers suggested that kinetic and

kinematic asymmetries for rhythmic lower limb

movements during pedalling were related in some

way to exercise intensity (Carpes et al., 2007a,

2007b; Sanderson, 1990). Among runners, experi-

ence was related to symmetry (Cavanagh, Pollock, &

Landa, 1977). Leg force asymmetries for knee

extension have been related to neural factors (Simon

& Ferris, 2008). However, to the best of our

knowledge, no previous study has addressed bilateral

assessment of muscle activation in participants with

different cycling skills during incremental and con-

stant load trials in an attempt to characterize

asymmetries in muscle activation between the pre-

ferred and non-preferred leg. Therefore, the aim of

the present study was to examine asymmetries in

muscle activation in cyclists and non-cyclists in two

experiments. Our main hypothesis was that asym-

metries in muscle activation might occur during

pedalling, which could in part be dependent on

cycling skill. The findings support similar muscle

activation between the preferred and non-preferred

leg for both cyclists and non-cyclists during the

incremental test.

Performance and muscle efficiency

Performance and muscle efficiency were not the main

variables in the experiments. However, these vari-

ables were important to identify differences between

cyclists and non-cyclists in the two experiments.

Cyclists presented generally higher scores of variables

related to performance ( _V O2max, maximal power

output, power/mass ratio, and power output eliciting

second ventilatory threshold) than non-cyclists. In

addition, even though previous reports suggest no

difference in gross efficiency between recreational

and competitive cyclists (Nickleberry & Brooks,

1996), the prolonged training (Chapman, Vicenzino,

Blanch, & Hodges, 2008) and physical adaptation of

cyclists (Boning, Gonen, & Maassen, 1984; Sidossis

et al., 1992) would support improved efficiency when

athletes are compared with non-cyclists. However,

the improvement in gross efficiency could also be

related to the preference of cyclists to pedal at higher

cadences and mechanical workloads (Coyle, Sidossis,

Horowitz, & Beltz, 1992).

Muscle activation

During incremental cycling to exhaustion, a pro-

gressive increase of motor unit recruitment over time

is expected (Jammes, Caquelard, & Badier, 1998;

Moritani et al., 1986). In both experiments in the

Table II. Coefficients of variation (expressed as percentages) for

EMG signals obtained in the constant load test of Experiment 1.

Muscle Leg CV (%)

Biceps femoris Preferred 23.2+8.1

Non-preferred 26.7+8.9

Gastrocnemius Preferred 20.9+4.5


Vastus lateralis Preferred 22.5+5.7


Note: Data are presented as group mean+ standard deviation for

each muscle and leg.


Figure 2. Mean and standard deviation root-mean-square (RMS)

values normalized by the maximal RMS observed in the

incremental test (RMS normalized) for biceps femoris, gastro-

cnemius (medial head), and vastus lateralis for the preferred (P)

and non-preferred (NP) leg of participants in Experiment 2.

Results from each muscle are presented for intensities of 40%,

60%, 80%, and 100% of maximal power output. For both legs,

RMS increased significantly as the exercise intensity increased

(#P50.05 between intensities), except for gastrocnemius. No

differences were observed between the preferred and non-

preferred leg.


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present study, for the preferred and non-preferred

leg, activation of the vastus lateralis and biceps

femoris increased significantly as the exercise in-

tensity increased. There was no difference in the

magnitude of muscle activation during the incre-

mental test between the preferred and non-preferred

leg, in both cyclists and non-cyclists. This does not

support asymmetries in force and torque previously

reported (Carpes et al., 2007a, 2007b; Sanderson,

1990) as being dependent on neural factors such as

the magnitude of muscle activation. Among non-

cyclists in Experiment 2, vastus lateralis reached

maximal root-mean-square values before the final

workload, which probably resulted from poor coordi-

nation in trying to sustain the cumulative workload

(Hug et al., 2004a), whereas cyclists in Experiment 1

showed improved neuromuscular function with train-

ing (Chapman et al., 2008; Hug, Decherchi, Mar-

queste, & Jammes, 2004b). The same was observed in

the biceps femoris, but in this case it also could be

attributed to use of clipless pedals, which may

improve the action of the biceps femoris during the

upstroke pedalling phase (Hug & Dorel, 2009). Small

changes in the activation of the gastrocnemius

medialis throughout an incremental workload have

been reported previously (Jorge & Hull, 1986) and

related to its role in energy transfer across the ankle

joint during pedalling (Hug & Dorel, 2009).

The similarity between legs supports the afore-

mentioned fatigue effects on the release of pathways

in sensorimotor areas (Kapreli et al., 2006). This

leads to an increase in common bilateral input that

could facilitate excitability and neural coupling by

inter-hemispheric cortical communication, which is

known to be a mechanism for the reduction of lateral

differences (Glass, 2001). Even though this mechan-

ism could satisfactory explain the symmetric muscle

activation during incremental cycling, the symmetry

during the constant load trials can be supported by

the reciprocal sensorimotor state of the contralateral

limb (Ting, Raasch, Brown, Kautz, & Zajac, 1998).

Therefore, fatigue and its effects is not the only factor

leading to symmetry in muscle activation.

The symmetry in magnitude of muscle activation is

also supported by mechanisms of inter-hemispheric

cortical communication avoiding larger lateral differ-

ences (Anguera et al., 2007; Seidler & Noll, 2008;

Teixeira & Caminha, 2003). However, kinetic

asymmetries previously identified (Carpes et al.,

2007a; Sanderson, 1990) might be related to bilateral

asymmetries in the variability of muscle activation,

which were observed in both our experiments and

could suggest variability in force production between

the legs. This mechanism is present in the upper

extremity (De Luca et al., 1986), but is not clear for

the lower limb.

The higher variability in the non-preferred leg of

cyclists in Experiment 1 suggests that motor re-

dundancy plays an important role in multiple

synergies and combinations of muscle actions for

the production of the same motor pattern (Hug,

Drouet, Champoux, Couturier, & Dorel, 2008). On

the other hand, during the incremental maximal test

of Experiment 2, no clear influence of a preference

on EMG variability was observed among the non-

cyclists. In Experiment 1, the variability observed

between bi-articular (biceps femoris, gastrocnemius

medialis) and mono-articular (vastus lateralis)

muscles was consistent with the literature (Ryan &

Gregor, 1992). Asymmetries in EMG group varia-

Table III. Coefficients of variation (expressed as percentages) for EMG signals obtained in the incremental test of Experiment 2.

Muscle Leg

Intensities (% of maximal power output)

40% 60% 80%

Biceps femoris Preferred 22.1+ 5.0 24.8+5.6 10.6+ 1.1

Non-preferred 36.1+ 14.0* 32.4+11.9 26.5+ 7.6*

Gastrocnemius Preferred 28.8+ 7.5* 17.9+3.3 13.2+ 1.7*

Non-preferred 14.4+ 2.0 16.3+3.4 10.9+ 1.2

Vastus lateralis Preferred 27.0+ 9.0* 29.2+10.7 21.2+ 5.8*

Non-preferred 5.2+ 0.3 23.8+7.1 14.9+ 2.5

Note: The 100% intensity was not considered due to a standard deviation equal to zero in most cases. Data are presented as group

mean+ standard deviation for each muscle, intensity, and leg.


Table IV. Coefficients of variation (expressed as percentages) for

EMG signals obtained in the constant load test of Experiment 2.

Muscle Leg CV (%)

Biceps femoris Preferred 42.0+13.4


Gastrocnemius Preferred 29.1+3.5

Non-preferred 39.4+11.1*

Vastus lateralis Preferred 17.1+3.9

Non-preferred 41.0+11.1*

Note: Data are presented as group mean+ standard deviation for

each muscle and leg.



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bility were observed only during the incremental test

of cyclists in Experiment 1. In the sub-maximal

test, no significant differences between legs were

observed. Lower muscle activation variability in

cyclists is consistent with improved muscle synergy

as an effect of long-term training (Chapman et al.,

2008) and results from repeated practice leading to

more precise and accurate ability for force control

(Bernardi, Solomonow, Nguyen, Smith, & Baratta,

1996). Indeed, the lower and similar variability

between legs could offer some advantages for

metabolic cost reflecting higher efficiency, such as

previously reported for walking (Goble, Marino, &

Potvin, 2003; Reisman, Block, & Bastian, 2005).

Further studies should address the influence of leg

preference on the variability of muscle activation,

which appeared to be somewhat influenced by a

lateral preference. One limitation of the present

study was that force applied on the pedals could not

be measured. This would address whether differ-

ences in muscle activation group variability were

related to differences in force production.

Conclusion

The present results suggest that previous reports of

pedalling force asymmetries in favour of the preferred

leg during pedalling are not directly related to the

magnitude of muscle activation. The reciprocal

sensorimotor state of the contralateral limb appears

to fundamentally support equality in muscle activa-

tion during constant load pedalling in participants

with different cycling skills. The influence of varia-

bility of muscle activation on pedalling asymmetry

merits further investigated.

Acknowledgements

This research was supported by an International

Society of Biomechanics (ISB) Travel Award to the

first author, and partially supported by the University

of Calgary and CAPES. The authors greatly appreci-

ate the contribution of Dr. Brian MacIntosh and

Dr. Marco Vaz for study design and data analysis.

The authors also thank Giovani Cunha, Geoff Smith,

and Erica Enevold for technical support during data

acquisition. Many thanks also to the participants for

agreeing to take part in the study.

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Influence of leg preference on bilateral muscle activation during cycling